Rafael Muñoz-Carpena

Modeling hydrology and sediment transport in vegetative filter strips

The performance of vegetative filter strips is governed by complex mechanisms. Models can help simulate the field conditions and predict the buffer effectiveness. A single event model for simulating the hydrology and sediment filtration in buffer strips is developed and field tested. Input parameters, sensitivity analysis, calibration and field testing of the model are presented. The model was developed by linking three submodels to describe the principal mechanisms found in natural buffers: a Petrov‐Galerkin finite element kinematic wave overland flow submodel, a modified Green‐Ampt infiltration submodel and the University of Kentucky sediment filtration model for grass areas. The new formulation effectively handles complex sets of inputs similar to those found in natural events. Major outputs of the model are water outflow and sediment trapping on the strip. The strength of the model is a good description of the hydrology within the filter area, which is essential for achieving good sediment outflow predictions or trapping efficiency. The sensitivity analysis indicates that the most sensitive parameters for the hydrology component are initial soil water content and vertical saturated hydraulic conductivity, and sediment characteristics (particle size, fall velocity and sediment density) and grass spacing for the sediment component. A set of 27 natural runoff events (rainfall amounts from 0.003 to 0.03 m) from a North Carolina Piedmont site was used to test the hydrology component, and a subset of nine events for the sediment component. Good predictions are obtained with the model if shallow uniform sheet flow (no channelization) occurs within the filter. q 1999 Elsevier Science B.V. All rights reserved.

UNCERTAINTY IN TMDL MODELS

Although the U.S. Congress established the Total Maximum Daily Load (TMDL) program in the original Clean Water Act of 1972, Section 303(d), it did not receive attention until the 1990s. Currently, two methods are available for tracking pollution in the environment and assessing the effectiveness of the TMDL process on improving the quality of impaired water bodies: field monitoring and mathematical/computer modeling. Field monitoring may be the most appropriate method, but its use is limited due to high costs and extreme spatial and temporal ecosystem variability. Mathematical models provide an alternative to field monitoring that can potentially save time, reduce cost, and minimize the need for testing management alternatives. However, the uncertainty of the model results is a major concern. Uncertainty is defined as the estimated amount by which an observed or calculated value may depart from the true value, and it has important policy, regulatory, and management implications. The source and magnitude of uncertainty and its impact on TMDL assessment has not been studied in depth. This article describes the collective experience of scientists and engineers in the assessment of uncertainty associated with TMDL models. It reviews sources of uncertainty (e.g., input variability, model algorithms, model calibration data, and scale), methods of uncertainty evaluation (e.g., first-order approximation, mean value first-order reliability method, Monte Carlo, Latin hypercube sampling with constrained Monte Carlo, and generalized likelihood uncertainty estimation), and strategies for communicating uncertainty in TMDL models to users. Four case studies are presented to highlight uncertainty quantification in TMDL models. Results indicate that uncertainty in TMDL models is a real issue and should be taken into consideration not only during the TMDL assessment phase, but also in the design of BMPs during the TMDL implementation phase. First-order error (FOE) analysis and Monte Carlo simulation (MCS) or any modified versions of these two basic methods may be used to assess uncertainty. This collective study concludes that a more scientific method to account for uncertainty would be to develop uncertainty probability distribution functions and transfer such uncertainties to TMDL load allocation through the margin of safety component, which is selected arbitrarily at the present time. It is proposed that explicit quantification of uncertainty be made an integral part of the TMDL process. This will benefit private industry, the scientific community, regulatory agencies, and action agencies involved with TMDL development and implementation.

Exploring vulnerability of coastal habitats to sea level rise through global sensitivity and uncertainty analyses

Changes in coastal habitats brought about by climate change have the potential to cause population decline of shoreline dependent organisms. In particular, sea level rise associated with climate change can drastically affect wetlands and beaches which are important foraging and nesting areas of these organisms. SLAMM 5 (Sea Level Affecting Marshes Model) is widely used to simulate wetland conversion and shoreline modification for the purpose of habitat vulnerability assessment and decision making, but concerns regarding the suitability of the model due to the uncertainty involved in selecting many of the models empirical input parameters have been expressed. This paper applies a generic evaluation framework consisting of a state-of-the-art screening and variance-based global sensitivity and uncertainty analyses to simulate changes in the coastal habitats of the barrier island in Eglin Air Force Base, Florida in order to: (1) identify the important input factors and processes that control SLAMM 5s output uncertainty; (2) quantify SLAMM 5s global output uncertainty and apportion it to the direct contributions and interactions of the important input factors; and (3) evaluate this new methodology to explore the potential fate of the coastal habitats of the study area. Results showed that four input factors (DEM vertical error for the lower elevation range, historic trend of sea level rise, accretion, and sedimentation rates) controlled 88-91% of SLAMM 5s output variance in predicting changes in the beach habitat of Eglin Air Force Base. The most dominant processes governing the fate of the coastline of the study area were inundation (i.e. reduction in elevation due to sea level rise) and accretion/sedimentation. Interestingly, for lower elevation habitats (salt marsh, tidal flat, and beach), results showed possible gain or loss of these habitats depending on the relative strength of these processes resulting from the combination of input factors within their proposed uncertainty ranges. Higher-elevation habitats (swamps and inland fresh marsh) showed decrease in area over 100 years of simulation. These findings are important to implement managerial schemes in the area to protect threatened Plover birds (Charadrius sp.) communities. This generic model evaluation framework is model-independent and can be used to evaluate a wide range of environmental models.

A design procedure for vegetative filter strips using VFSMOD-W

Although vegetative filter strips (VFS) are a common BMP used for runoff sediment control, there is currently no widely accepted objective design criteria available to select optimal construction characteristics (filter length, width, slope, vegetation) needed to achieve a desired sediment reduction. A design procedure for VFS using VFSMOD-W is presented. VFSMOD, the main component of VFSMOD-W, is a field-scale, mechanistic, storm-based model developed to route the incoming hydrograph and sedigraph from an adjacent field through a VFS and to calculate the resulting outflow, infiltration, and sediment trapping efficiency. A front-end model, UH, was developed and added to VFSMOD-W to generate the necessary source area design inputs for VFSMOD. For each design storm, UH generates a rainfall hyetograph, a runoff hydrograph, and sediment loss from the source area using a combination of the NRCS curve number method, the unit hydrograph, and the modified Universal Soil Loss Equation based on topography, land use, and soil type. With these inputs, a set of response curves, i.e., sediment and runoff reduction vs. filter construction characteristics, can be developed from VFSMOD-W outputs for a given design scenario. To illustrate this procedure, a design case was presented where the goal was to obtain a 75% runoff sediment reduction for conditions similar to those of the North Carolina Piedmont region. In addition to two soil types present in the area, the range of conditions used in the analysis included two design alternatives (one concentrating field runoff in a narrower filter), four design storms with 1 to 10 year return periods, and buffer lengths ranging from 1 to 100 m. For the range of design storms considered, the optimal filter lengths obtained were 1 to 4 m for the sandy clay soil and 8 to 44 m for the clay. The results show that in some cases current environmental regulations pertaining to filter lengths in the area will not be sufficient. This application case clearly illustrates the importance of using an objective design procedure based on the specific location characteristics when implementing VFS as an effective off-site BMP.

FIELD EVALUATION OF THE NEW PHILIP-DUNNE PERMEAMETER FOR MEASURING SATURATED HYDRAULIC CONDUCTIVITY

One of the most sensitive parameters in hydrological models, the saturated hydraulic conductivity (Ks), is also one of the most problematic measurements at field scale in regard to variability and uncertainty. The performance of a new type of simple and inexpensive field permeameter, the Philip-Dunne permeameter (PD), is compared with two established alternatives, the laboratory constant head permeameter (LP) and the field Guelph permeameter (GP). A PD prototype, a protocol of usage, and a numerical routine to find Ks were developed and tested on a 70-point array laid out on an 850-m2 volcanic soil plot. A power transformation was applied to the raw data using the three methods, and the transformed data were shown to be normally distributed. The LP and GP data were better described by a log-normal distribution, whereas the PD data could also be approximated with a power-normal distribution. A factor of 3 was found to relate PD, LP, and GP hydraulic conductivity estimates, E[Ks], such that E [Ks-PD] ≌ 3 E [Ks-LP];E [Ks-LP] ≌ 3 E [Ks-GP]. Such differences may be explained by the different water infiltration geometries and sample wetted volume for the three methods. The PD has advantages over the other two methods in terms of personnel involved, preparation time, and ease of operation. Additionally, the PD methodology required a smaller number of samples (41% less than GP and 69% less than LP) to estimate the population mean Ks. Both PD and GP also give the suction at the wetting front, an important parameter that characterizes the unsaturated flow properties of the soil.

Numerical Approach to the Overland Flow Process in Vegetative Filter Strips

Agricultural and other disturbed lands contribute to non-point source pollution of water bodies (streams and lakes). Vegetative filter strips (VFS) are often recommended to reduce off-site impacts. Design guidelines to optimize the performance of VFS are not readily available. A process-based model is presented to simulate the hydrology of a Vegetative Filter Strip for a given event. The model consists of a quadratic finite element overland flow submodel, based on the kinematic wave approximation, coupled with an infiltration submodel based on a modification of the Green-Ampt equation for unsteady rainfall. The model is used to study the effect of soil type, slope, surface roughness, buffer length, storm pattern and field inflow on the VFS performance. Filter performance, i.e., reduction of the runoff volume, velocity and peak, is higher for denser grass cover, smaller slopes and soils with higher infiltration capacity. Time to peak(s) depended mainly on the roughness-slope combination.

Evaluating, interpreting, and communicating performance of hydrologic/water quality models considering intended use: A review and recommendations ☆

Abstract Previous publications have outlined recommended practices for hydrologic and water quality (H/WQ) modeling, but limited guidance has been published on how to consider the projects purpose or models intended use, especially for the final stage of modeling applications – namely evaluation, interpretation, and communication of model results. Such guidance is needed to more effectively evaluate and interpret model performance and more accurately communicate that performance to decision-makers and other modeling stakeholders. Thus, we formulated a methodology for evaluation, interpretation, and communication of H/WQ model results. The recommended methodology focuses on interpretation and communication of results, not on model development or initial calibration and validation, and as such it applies to the modeling process following initial calibration. The methodology recommends the following steps: 1) evaluate initial model performance; 2) evaluate outliers and extremes in observed values and bias in predicted values; 3) estimate uncertainty in observed data and predicted values; 4) re-evaluate model performance considering accuracy, precision, and hypothesis testing; 5) interpret model results considering intended use; and 6) communicate model performance. A flowchart and tables were developed to guide model interpretation, refinement, and proper application considering intended model uses (i.e., Exploratory, Planning, and Regulatory/Legal). The methodology was designed to enhance application of H/WQ models through conscientious evaluation, interpretation, and communication of model performance to decision-makers and other stakeholders; it is not meant to be a definitive standard or a required protocol, but together with recent recommendations and published best practices serve as guidelines for enhanced model application emphasizing the importance of the models intended use.

Effect of solution chemistry on multi-walled carbon nanotube deposition and mobilization in clean porous media

There are increasing concerns over the environmental impact and health risks of carbon nanotubes (CNTs) because they may be released into soil and groundwater systems. The present work systematically investigated the transport, deposition, and mobilization behaviors of multi-walled carbon nanotubes (MWNTs) in saturated columns packed with acid-cleaned glass beads and quartz sand of two different grain sizes. Combined effects of pH (5.6 and 10) and ionic strength (IS: DI water, 1mM, and 10mM) on the fate and transport of the MWNTs in the columns were examined. MWNTs were relatively mobile in all the tested conditions with DI water as the experimental solution. Their deposition in the saturated porous media, however, was very sensitive to solution chemistry, particularly IS. Slight increase in solution IS (1 mM) caused strong deposition of MWNTs in both quartz sand (>44%) and glass beads (>39%). Mobilization experimental results indicated that most of the MWNT attachment (>73%) to the porous media was irreversible and reduction in solution IS only caused a small portion of re-entrainment (<27%) of deposited MWNT for all the tested conditions. This indicates that more MWNTs are trapped in the primary minimum, although the deposition of MWNTs in saturated porous media occurs in both primary and secondary minimum. It is suggested that, under unfavorable conditions, weak associated MWNTs in the secondary minimum may be transferred into the primary minimum due to the effect of hydrodynamic force and/or local favorable sites associated with surface heterogeneity.

Brief history of agricultural systems modeling

Agricultural systems science generates knowledge that allows researchers to consider complex problems or take informed agricultural decisions. The rich history of this science exemplifies the diversity of systems and scales over which they operate and have been studied. Modeling, an essential tool in agricultural systems science, has been accomplished by scientists from a wide range of disciplines, who have contributed concepts and tools over more than six decades. As agricultural scientists now consider the “next generation” models, data, and knowledge products needed to meet the increasingly complex systems problems faced by society, it is important to take stock of this history and its lessons to ensure that we avoid re-invention and strive to consider all dimensions of associated challenges. To this end, we summarize here the history of agricultural systems modeling and identify lessons learned that can help guide the design and development of next generation of agricultural system tools and methods. A number of past events combined with overall technological progress in other fields have strongly contributed to the evolution of agricultural system modeling, including development of process-based bio-physical models of crops and livestock, statistical models based on historical observations, and economic optimization and simulation models at household and regional to global scales. Characteristics of agricultural systems models have varied widely depending on the systems involved, their scales, and the wide range of purposes that motivated their development and use by researchers in different disciplines. Recent trends in broader collaboration across institutions, across disciplines, and between the public and private sectors suggest that the stage is set for the major advances in agricultural systems science that are needed for the next generation of models, databases, knowledge products and decision support systems. The lessons from history should be considered to help avoid roadblocks and pitfalls as the community develops this next generation of agricultural systems models.

Physical properties of “sorriba”-cultivated volcanic soils from Tenerife in relation to andic diagnostic parameters

In volcanic regions, soils containing both noncrystalline materials and layer silicates are widespread. Although the respective contribution of these components to soil physical behaviours is difficult to quantify, it is an important issue in the Canary Islands, where Andisols and andic soils are transported to the low lands for cultivation (‘‘sorriba’’). In this new soil environment, salinisation and sodification processes, induced by irrigation and heavy fertilisation, are potential threats to soil degradation. The purpose of this work was to evaluate some relevant physical properties of the sorriba-cultivated volcanic soils from Tenerife in order to relate them to salinity and sodicity soil conditions, amounts of layer silicates and remaining andic properties, characterised by: bulk density (qb), Al and Fe extracted with ammonium oxalate (Alo ,F eo) and P retention. An Andisol under forest was included in the study as a representative natural reference. Clay dispersion, water release curves and saturated hydraulic conductivity, Ks, were the selected physical properties. Four distinctive types of water release curves were identified, showing sandy behaviour at low suctions while retaining large water holding capacity at large suctions. The van Genuchten parameters helped to differentiate these curves and identify the main pore-size ranges. Under certain combinations of exchangeable cations distribution, salinity and clay mineralogy, very low Ks values were observed for Alo contents lower than 3%. The results suggest that the aggregating effect of Alo (allophanes) could not counterbalance soil structure deterioration. Furthermore, only a multivariable analysis carried out on chemistry, mineralogy and physical data had the merit to classify the studied sorriba-cultivated volcanic soils in terms of soil quality and soil functioning. D 2003 Elsevier Science B.V. All rights reserved.